{"id":32638604,"url":"https://github.com/margotrud/shopping_assistant","last_synced_at":"2026-04-18T11:32:31.262Z","repository":{"id":335283399,"uuid":"1138275749","full_name":"margotrud/Shopping_assistant","owner":"margotrud","description":"NLP-driven lipstick recommender that turns free-text preferences into color-constrained rankings.","archived":false,"fork":false,"pushed_at":"2026-02-10T11:21:05.000Z","size":17676,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"master","last_synced_at":"2026-02-10T15:53:35.605Z","etag":null,"topics":["color-science","lab-color-space","nlp","python","recommendation-system","streamlit"],"latest_commit_sha":null,"homepage":"https://github.com/margotrud/Shopping_assistant","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/margotrud.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2026-01-20T13:16:52.000Z","updated_at":"2026-02-10T11:21:08.000Z","dependencies_parsed_at":"2026-01-30T02:01:31.280Z","dependency_job_id":null,"html_url":"https://github.com/margotrud/Shopping_assistant","commit_stats":null,"previous_names":["margotrud/shopping_assistant"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/margotrud/Shopping_assistant","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/margotrud%2FShopping_assistant","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/margotrud%2FShopping_assistant/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/margotrud%2FShopping_assistant/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/margotrud%2FShopping_assistant/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/margotrud","download_url":"https://codeload.github.com/margotrud/Shopping_assistant/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/margotrud%2FShopping_assistant/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31966969,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-18T00:39:45.007Z","status":"online","status_checked_at":"2026-04-18T02:00:07.018Z","response_time":103,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["color-science","lab-color-space","nlp","python","recommendation-system","streamlit"],"created_at":"2025-10-31T02:03:10.750Z","updated_at":"2026-04-18T11:32:31.253Z","avatar_url":"https://github.com/margotrud.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cp align=\"center\"\u003e\n  \u003cimg src=\"assets/demo.png\" width=\"900\"\u003e\n\u003c/p\u003e\n\n# Shopping Assistant — Color-Aware Recommendation from Natural Language\n\nThis project is a color-aware recommendation system that focuses on the interpretation\nand ranking stages of cosmetic shade selection, starting from free-text user preferences.\n\nIt parses natural language constraints (e.g. brightness, warmth, exclusions), resolves\ncolor anchors in Lab space, builds adaptive candidate pools, and ranks products using\nfully deterministic, test-backed logic. The project is designed as a reproducible\nportfolio system, not a production or end-to-end service.\n\n---\n\n## Key features\n\n- Natural language preference interpretation with explicit constraint contracts\n- Domain-aware color anchoring and adaptive candidate pooling\n- Calibrated Lab-space scoring with deterministic tie-breaking\n- Fully test-covered core logic (pytest)\n- Streamlit demo application for interactive exploration\n\n---\n\n## Project structure\n\n```\nsrc/Shopping_assistant/     # Core Python package (NLP, color, scoring, recommendation)\nScripts/                   # Offline asset generation and diagnostics (not required at runtime)\ndata/                      # Versioned runtime assets (lexicons, anchors, calibration)\ntests/                     # Pytest-only unit and contract tests\nstreamlit_app/             # Demo application\n```\n\n---\n\n## Quickstart\n\n```bash\npip install -r requirements.txt\npip install -e .\npytest -q\nstreamlit run streamlit_app/Home.py\n```\n\nOptional demo:\n```bash\nstreamlit run streamlit_app/Home.py\n```\n\n---\n\n## Data \u0026 assets\n\nAll runtime assets are versioned under `data/`.\nScripts used to generate or validate these assets are documented in `Scripts/README.md`.\n\n### Dataset limitations\n\nThe included dataset is a truncated subset of the original catalog.\nIt is intended to make the application runnable and illustrate the\ninterpretation and ranking logic, not to reflect final recommendation quality.\n\nAs a result, some rankings or explanations may appear less accurate\nthan in the full internal setup.\n\n---\n\n## Scope and intent\n\nThis repository prioritizes clarity, determinism, and testability over production concerns\n(scaling, latency, serving infrastructure).\nIt is intended to demonstrate applied data science, NLP interpretation, and color-aware\nrecommendation design.\n\n---\n\n## License\n\nMIT\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmargotrud%2Fshopping_assistant","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmargotrud%2Fshopping_assistant","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmargotrud%2Fshopping_assistant/lists"}